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Variations in abundance and distribution of fish species in Lake
Mutirikwi, Zimbabwe
Barbra Masungaa, S. Kusangayaa, LRM Nhamo, W. Zhakataa
a
Department of Geography and Environmental Science, University of Zimbabwe, P. O. Box
MP167, MT Pleasant, Harare.
b
Department of Biological Science, University of Zimbabwe, P. O. Box MP167, MT Pleasant,
Harare.
_____________________________________________________________
Abstract
Loss of biodiversity that is now occurring worldwide is the foremost tragedy of our
era because it is permanently altering our environment. The problem is particularly
acute in freshwater environments because they are in most cases ignored. Due to the
magnitude of the problem of species decline, calls to save endangered species are now
being replaced by calls to save endangered ecosystems. Worldwide, fisheries are
undergoing a paradigm shift whereby new issues such as monitoring and analyses of
spatio-temporal factors including variations in distribution, abundance, regulatory
zoning and deterioration of ecosystems are taking the forefront. Thus this study was
aimed at evaluation the loss of biodiversity, specifically fish species from lake
Mutirikwi, Zimbabwe. Field studies included setting and catching the fish using nets
of different sizes and subsequent measurement and analysis of various fish
characteristics including length, weight, sex, breeding stages, time of the year,
preference of certain depth range and lake water depth level. These characteristics
were then used to determine the abundance and spatio-temporal distribution of the
fish species in the lake. Eleven fish species (6 indigenous and 5 introduced) were
captured, with the most common ones being Clarius gariepinus (53%),
Serranochromis robustus Tilapia rendalli (12.8%) Mormyrus longirostris (17.9%)
whilst the least common being Barbus aeneous (0.09%). The peak catch per unit
effort (cpue) for the five years was recorded in the following months November 2001,
November 2002, March 2003, September 2004 and December 2005. Clarius
gariepinus dominated the catch (53.9%) followed by m. longirostris (17.9%), t.
rendalli (12.8%) and S .robustus (8.4%). The lowest cpue was for b. aenus which
yielded 0.09%. The management implications include the need for fisheries scientists
and the communities to work together in preventing threats from over fishing. There
is need to revise the closed seasons of the lake so as to stop over fishing some of the
species that may be in the breeding stages. On the other hand, whilst the communities
are benefiting there is need to teach them on ways to sustainable harvesting of their
fishery resources so that future generations will also benefit from the same Lake.
Keywords: biodiversity, fish, abundance, freshwater environment
Corresponding Author: E-mail: [email protected]
1 INTRODUCTION
Water has a central role in mediating global-scale ecosystem processes, linking
atmosphere, lithosphere and biosphere by moving substances between them and
enabling chemical reactions to occur. At the Earth's surface, freshwater forms the
habitat of a large number of species. These aquatic organisms and the ecosystems in
which they participate represent a substantial proportion of the Earth's biological
diversity. Of the world’s 1,868,000 species, 44,000 are described as coming from
freshwater ecosystems (Reaka-Kudla 1997). This figure may seem small compared to
other ecosystems but considering that freshwater ecosystems occupy only 0.8% of the
earth’s surface it translates into an incredibly species-rich group of habitats. An
estimated 42% of the world’s fishes live in freshwater (McAllister et al. 1997; Froese
and Pauly 2004). With the continuing description and discovery of more freshwater
fish each year it is now estimated that there are over 12,000 primary freshwater
species and a further 2,680 brackish or diadromous species (Froese and Pauly 2004).
The International Convention on Biological Diversity encourages parties to identify
and monitor activities that harm biodiversity and protect biodiversity through a range
of measure such as creation of protected areas and implementation of regulations and
incentives aimed at ensuring its sustainable use. In Zimbabwe, many large Lakes are
protected through having recreational parks that are described as protected areas.
These are mainly around dams like Lake Kariba, Mutirikwi, Chivero, Manyame,
Manjirenji, and Sebakwe.
Lake Mutirikwi was constructed mainly to supply water for irrigation purposes.
However, with time the Lake has become a major source of fish for the surrounding
communities and beyond. When the water is used for irrigation, large draw downs are
expected and this would result in fluctuating lake levels. It is unclear what effect
changes in lake level have on the relative abundance of the fish species. So, it is
argued in this study that hydrological variables like lake level, capacity, rainfall and
outflow are responsible for some of the variations in abundance and distribution of
fish species in Lake Mutirikwi. Gasith and Gafny (1992) argued that water level
fluctuations, either man made or natural affect habitat availability in Lakes. Gotceitas
and Godin (1992), Imre et al (2002), Reinhardht (1999), Sloman et al (2001) showed
that seasonal fluctuations in the water level determine the presence or absence of any
fish species in a temporarily inundated area and also provoke complicated changes in
the community structure of the community. These changes thus can become a factor
in controlling spatio-temporal distribution of fish species. Sloman et al (2001, 2002)
found that unstable environmental conditions significantly altered dominance
structure of trout population that was stable under constant conditions.
Although there is a lot of literature on fisheries in Zimbabwe, fisheries management
researches were mainly carried out in Lake Kariba (Mandima, 1995; Sanyanga, 1995,
1997; Chifamba, 1996; 2002; 2004; Mutsambiwa, 1998 and Wanink, 1996). This
shows that fisheries information is readily available for Lake Kariba. Lake Mutirikwi
is one of the least scientifically studied Lakes yet it is the largest inland Lake in the
country. The last detailed study on Lake Mutirikwi was done soon after impoundment
( by Junor,1969) but a lot of changes have taken place from the riverine conditions to
the lacustrine conditions now established hence the need to study variations in
abundance of fish species in Lake Mutirikwi. So in this study it is hypothesised that
there exists some size-depth pattern in the vertical distribution of fish species in Lake
2
Mutirikwi.The aim of the study is to investigate the spatial and temporal variations in
abundance and distribution of fish species in Lake Mutirikwi. Specifically the
research seeks to: (1) determine temporal variations in abundance of fish species in
Lake Mutirikwi, (2) determine hydrological factors affecting relative abundance of
fish species in Lake Mutirikwi, (3) determine vertical size distribution of fish species
in Lake Mutirikwi .
2 MATERIALS AND METHODS
2.1 Description of Study Area
Lake Mutirikwi, formed by the construction of a dam wall at the confluence of
Mutirikwi and Shagashi rivers is the largest inland Lake in Zimbabwe. It lies at an
altitude between 1000 and 1040m above sea level on the Central African plateau. It is
at latitude 200 131S and longitude 300 01E and is 32km South East of Masvingo town.
At its maximum, it has a surface area of 9 105 hectares and a carrying capacity of 1
378.082*106m3. The shoreline perimeter of the Lake is 238 km. The dam wall has a
height of 63.1 meters and the length of this wall is 309 meters. The Lake took 14
years to fill. Its catchment area covers 3 989km2. Figure 1 shows the location of the
study area.
Figure 1: Location of Lake Mutirikwi in Zimbabwe
The Lake was constructed in 1960 with the aim of providing water for extensive
irrigation. In 1967, the Lake was proclaimed part of the National Park. In addition to
its function as a reservoir, it now provides facilities for boating, angling and
commercial fishing by means of gill nets. Nineteen fish species have been recorded
from this Lake with eleven of them being indigenous and eight introduced
(Mangwaya, 1997). Table 1 is a summary of fish species found in Lake Mutirikwi.
Table 1: List of fish species found in Lake Mutirikwi
2.2 Methods
Historical data on fisheries was collected from Lake Mutirikwi fisheries research
station. The data was from September 2000 to June 2006 for six bays which were
Sikato, Bompsty, Vutami, Basuto, Bimha and Goose. The fish were sampled on a
monthly basis from these bays. Gillnets were set at sunset (6:00 in the evening) and
removed at sunrise (6:00 in the morning). These gill nets were top set (0-4m), deepset (4-8m) and bottom set (8-12m). The fish catches were recorded according to
species, day caught, type of setting used, sex activity, size of gillnet, bay at which
fishing was carried out, length of fish species and weight of fish species. On sex
activity, sex of the fish species was recorded and gonad condition was inspected
visually to give a seven stage maturity scale which ranged from: inactive/immature,
inactive active, active, active ripe, ripe, ripe-running and spent. The monthly
experimental gill net data accumulated at Lake Mutirikwi fisheries research station
from their sampling programme is the largest and probably one of the most reliable
data series from Lake Mutirikwi. The routine is well incorporated into the activities of
3
Lake Mutirikwi Fisheries Research and the sampling design and methodology have
remained constant over the whole period such that it is safe to conclude that the data
base to a large extent represent the changes in relative abundance of the fish species in
Lake Mutirikwi. Hydrological variables: Lake level, capacity, outflow and rainfall
were obtained from Zimbabwe National Water Authority (ZINWA) Runde
Catchment. These variables were recorded daily.
The fish data and hydrological data were then entered into Microsoft Excel
spreadsheet. The relative abundance of the fish species was measured using catch per
unit effort (cpue) where this was calculated as the weight of fish caught per day. This
was calculated for the various fish species (i) using the formula [1].
Cpuei (g/day) = total mass of fish species i caught in a month/number of days fished in the month. [1]
Cpue can be used as an index of abundance of biomass of a fish stock (Karenge,
1993)
The number of fish in the breeding stage was calculated. The cpue for the various fish
species was then tested for normality so as to decide on the type of statistical testing
to use. Regression analysis was done between the number of breeding species and
cpue when the two were found to be significantly correlated and outliers were
removed.
For hydrological variables, a test for independence of the independent variables was
carried out. This was done by correlation analysis and this was done to reduce
redundancy. Spearman’s correlation analysis was applied since the data was not
normally distributed. The independent hydrological variables were then correlated
with cpue of the fish species. In situations where independent variables were
correlated, the variable with the highest explanatory power was chosen.
Vertical size distribution of fish species was found by using length data and the type
of setting at which the various sizes of fish species were caught. It was found if there
were significant differences in the size of fish species in the various types of settings.
3 RESULTS AND ANALYSIS
3.1 Relative fish abundance
A total of 3636 fish representing 11 species belonging to five families were caught in
the experimental gillnetting during the study period. Of these species 6 were
indigenous and 5 introduced. The dominant families were Claridae (54%), Cichlidae
(25%) and Mormyridae (19%). Common species among these included c.gariepinus
(53.9%), m.longirostris (17.9%) and t.rendalli (12.8%). Rare ones included b.aenus
which had 0.09%. Figure 2 below shows the variations in relative abundance of the
fish species from September 2000 to June 2006.
Figure 2: Relative abundance of fish species caught in Lake Mutirikwi.
4
The peak catch per unit effort for the five years was recorded in November 2001,
November 2002, March 2003, September 2004 and December 2005. Clarius
gariepinus dominated the catch until 2002 when it started to decline. The cpue for
c.gariepinus from 2000 to 2006 had a highest peak in 2001 (66.87%) and was lowest
in 2006 (36.35%). Manny Whitney test conducted showed that except between 2003
and 2004 where there was a significant (p<0.05) decline, there was no significant
(P>0.05) change in the catch per unit effort over the other consecutive years.
Regression of relative abundance of c.gariepinus fish with number of ripe fish of this
species shows a positive relationship between the number of ripe fish (Figure 3).71%
of the variance in relative abundance of c.gariepinus can be explained by breeding
stage of the fish species.
Figure 3: Regression of cpue of c.gariepinus on ripe species.
S.robustus and m.longirostris did not show any significant (p>0.05) changes in
relative abundance over the years. The number of ripe s.robustus caught was so few
that we could not establish the breeding periodicity. As for m.longirostris the breeding
period is from November to March but there exist no significant (p>0.05) correlation
between number of ripe fish and cpue.
T. rendalli’s cpue has been fuctuating over the time period with the highest cpue in
2005 (21.61%) and the lowest in 2002 (7.59%). Mann Whitney test conducted to test
if there were any significant differences in the cpue over the consecutive years
showed that there was a significant (p<0.05) rise in the cpue between 2004 and 2005.
Otherwise there was no significant(p>0.05) difference in the cpue for this fish species
for other years. The number of ripe fish caught was so few that we could not establish
the breeding periodicity for this fish species.
3.2 Hydrological data analysis
Table 2 shows the test of normality that was done on the data. It can be observed that
the data for m.longirostris, s.robustus, c.gariepinus, t.rendalli and rainfall is normally
distributed (p>0.05).
Table 2: Test of normality on fish species and hydrological data
The relationship between hydrological variables and relative abundance of fish
species was also evaluated. Table 3 below shows that Lake level and outflow are
significantly correlated with capacity. It also shows that these three variables are
significantly correlated with cpue of t.rendalli. All the other fish species show no
dependence on the hydrological variables.
Figure 4 below shows that there is a significant (p<0.05) relationship between cpue of
t.rendalli and capacity. The relationship is such that as the capacity increases the
relative abundance of t.rendalli decreases. Capacity explains 48% of the variance in
the relative abundance of t.rendalli in these bays.
Figure 4: Regression of cpue of t.rendalli on capacity
5
3.3 Vertical size distribution
It can be observed that the largest fish of c.gariepinus species are found at the top
(Mean length 54.71+_ 9.70cm) followed by deep set nets (mean length
52.39+_8.24cm) whilst the smallest are at the bottom (mean length 49.61+_7.41cm).
Manny Whitney test conducted to test if there were significant differences in the size
distribution of the fish species by depth showed that top set nets had significantly
(p<0.05) larger c.gariepinus than bottom and deep set nets and also that the deep set
nets had significantly (p<0.05) larger fish species than for bottom set nets (Figure 5).
Figure 5: Size distribution of c.gariepinus
As for m.longirostris, the box plot shows that the largest fish are caught with deep
set nets (mean length 39.17+-8.076cm), followed by top set nets (mean length
37.43+-7.006cm) and then the smallest are for bottom set nets (mean length
33.61+-5.127cm). Mann Whitney test conducted showed significant (p<0.05)
differences in the size of the fish species by depth (Figure 6).
Figure 6: Vertical size distribution of m .longirostris
S.robustus, showed no significant differences (p>0.05) in the size of fish caught
for deep net (mean length 34.08+-5.859cm) and top net (mean length 33.96+6.246cm) but these two types of settings had significantly (p<0.05) larger fish than
for deep set nets (Figure 7).
Figure 7: vertical size distribution of s.robustus
T.rendalli species also showed no significant difference between top (mean length
27.94+-4.42cm) and deep(mean length 27.82+-5.744cm) but these two settings had
significantly larger fish than bottom set nets (mean length 25.75+-6.011cm) (Figure
8).
Figure 8: Vertical size distribution of t.rendalli
4 DISCUSSION AND CONCLUSIONS
4.1 Relative fish abundance
The peak catches for c. garipepinus coincided with the time when most of this fish
species was breeding. A significant positive correlation between cpue and breding
periodicity(r=0.645, p=0.000 , r=0.617, p=0.000 for males and females respectively
and r=0.691, p=0.000 for both male and female) was found for c.gariepinus. The
breeding season was extending from November to February. The two peaks recorded
in 2003 (one in October and the other in December ) were one for the male and the
other one for the female. Regression of the relative abundance of c.gariepinus on the
number of ripe fish shows that 71% of the varianace in the relative abundance can be
6
explained by the breeding stage of the fish species. Sanyanga (1995) suggested that it
is possible that fish incease in activity during the spawning season, so their
catchability inceases since gill nets are passive gear. The highest peak for
m.longirostris recorded in April 2004 coincided with the time when most fish in the
breeding stage were caught. However, there was no significant correlation between
cpue and breeding periodicity (r=0.332, p=0.329, r=0.145, p=0.415). The species,
b.aenus was caught in small numbers because this species favours the riverine
conditions hence lower catches because the three bays are found in the lacustrine end.
4.2 Hydrology and fisheries
The results reveal a link between relative abundance of t.rendalli and dam capacity.
The significant inverse relationship between increased Lake level and falling relative
abundance may be due to the concentration of the fish species and their increasing
ease of capture. Since t.rendalli rely on vegetation for food and escape from
predation, an increased capacity would mean an increase in the area inundated and
this can possibly lead to an increase in the area the species would find refuge from
predation thus leading to a decrease in the fish that can be caught. Donnelly (1969)
supports this by finding that when rooted aquatics are established in a Lake, survival
of juvenile tilapia increases greatly. In Lake Turkana, Kenya, Kolding (1993) found
peak production years of tilapias associated with years of peak rises in lake level.
4.3 Vertical size distribution
What can be noted for the four fish species is that, the smallest are caught using
bottom set nets. So, larger fish are not found at the bottom but either at the top or
middle layer. Power (1984), Schlosser (1988) and Harvey (1991) support this by
finding that it is primarily large fish that avoid shallow water when the risk of
predation is high. Large fish increase their use of shallow water when the risk of
predation is low (e.g.) at night. This is probably why large c.gariepinus fish species
are found in the top set nets at night. The terrestrial predators would not be active
during the night that the risk of predation of these large fish is reduced. These
terrestrial predators often prefer large fish (Power, Dudley and Cooper, 1989, Harvey
and Stewart, 1991) and are active during the day.
The other factor that may affect the size distribution of the fish species include
interference among the various species and also interference between the same species
which are of different sizes. This interference may have led to bigger fish species of
m.longirostris being found at the deep net zone where they would be avoiding
c.gariepinus which may be a potential predator at the surface. This interference may
also have led to displacement of the smaller c.gariepinus species by the larger
c.gariepinus species such that we would be having a size-depth distribution of the
same species. The same applies for m.longirostris, t.rendalli and s. robustus where the
smaller species may be displaced from their depth zone by the larger species so as to
avoid exploitative competition.
4.4 Management implications
The relationship between capacity and relative abundance of t.rendalli suggests that
monitoring Lake levels and capacity could give a rough indication of the fishery
situation in Lake Mutirikwi. There is need to reach a compromise between supplying
water for irrigation and maintaining Lake levels that would make harvesting of
t.rendalli sustainable. Otherwise if we draw water for irrigation without considering
7
the fate of t.rendalli will risk losing the species. In order to minimise the risk of losing
t.rendalli due to falling Lake levels induced by abstraction, efforts should be made to
prevent Lake level from falling during spawning period because a fall in Lake level
will expose the newly spawned juveniles to predation.
Since the largest fish are found either at the top or in deep set nets, there should be
regulations on minimising the number of bottom set nets that can be laid in the Lake.
This will enable the smaller fish to grow to a larger size before they are caught so as
to minimize recruitment over fishing.
5 REFERENCES
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annual report 2004 of Proceedings of the ULKRS Seminar series,
Chimbari,M.J and Phiri,C., University of Zimbabwe, 16-19
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300.
Harvey, B.C .1991. Interactions among stream fishes; predator induced habitat shifts
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Harvey, B.C and Stewart, A. J. 1991: Fish size and depth relationship in headwater
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Imre, I. Grant, J. W. A. Keeley, E.R, 2002. The effect of visual isolation on territory
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(Lacepede,1802) in lake Kyle, Rhodesia, Arnoldia, 26(6) 1-21
Karenge, L.P. and Kolding, J. 1995, On the relationship between hydrology and
fisheries in Lake Kariba, Central Africa. Fish. Res., 22:205-226.
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predators, depth and body size. Freshwater biology 43(1) 75-83
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Kariba, Zimbabwe, Annual report of Proceedings of the ULKRS Seminar
series 1995, Mandima,J.J., University of Zimbabwe,33-36
Mangwaya, G. 1997. A survey of fish fauna in lake Mutirikwi, Department Of
National Parks and Wildlife Managemnt, Harare.
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McAllister, D. E., Hamilton, A. L. and Harvey, B., 1997. Global freshwater
biodiversity: striving for the integrity of freshwater ecosystems. Sea Wind Bulletin of Ocean Voice International 113: 1–140.
Power, M.E., Dudley, T.L., and Cooper, S.D .1989: Grazing catfish, birds and
attached algae in a Panamanian stream, Environmental biology of fishes
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rain forests. In: M. L.Reaka-Kudla, D. E. Wilson, and E. O. Wilson eds,
Biodiversity II: Understanding and protecting our biological resources.
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coho salmon Oncorhynchus kisutch and provides growth opportunities for
risk-prone individuals. Can J Fish Aquat Sci 56:1206–1212.
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Sanyanga, R., 1996, The inshore fish populations of Lake Kariba with reference to the
biology of Synodontis zambezensis (Peters, 1852). Doctoral thesis, Dept. of
Systems Ecology, Stockholm University,
Schlosser, I. J., 1988: Predation risk and habitat selection by two size classes of
stream cyprinids: experimental tests of an hypothesis, Oikos 52, 36-40
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environmental perturbation on the social behaviour and physiological function
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9
TABLES
Table 3: List of fish species found in Lake Mutirikwi
Family
Aguillidae
Species
Anguilla
nebulosa
labiata
Anguilla mossambica
Barbus trimaculatus
Barbus radiatus
Barbus paludinosis
Barbus lineoma culatus
Barbus aeneous
Labeo cylindricus
Mesobola brevianalis
Cyprinidae
Mormyridae
Cichlidae
Mormyrus longirostris
Serranochromis
robustus
Tilapia sparrmananaii
Tilapia rendalli
Oreochromis macrochir
Oreochromis placidus
Oreochromis
mossambicus
Common name
Status
African mottled eel
Indigenous
Three spot Barb
Beira Barb
Sraitfin Barb
Linespotted Barb
Indigenous
Indigenous
Indigenous
Indigenous
Yellowfish
Redeye labeo
River sardine
Bottlenose
Nembwe (largemouth
bream)
Banded tilapia
Introduced
Indigenous
Introduced
Introduced
Introduced
Redbreast bream
Greenheaded bream
Indigenous
Introduced
Black tilapia
Introduced
Mozambique tilapia
Indigenous
Sharptooth catfish
Largemouth bass
Indigenous
Introduced
Indigenous
Clariidae
Centrachidae
Clarias gariepinus
Micropterus salmoides
(Source: Mangwaya, 1997)
Table 4: Test of normality on fish species and hydrological data
m.longirostris
t.rendalli
s.robustus
c.gariepinus
m.salmoides
Level
Capacity
%FSC
Outflow
Rainfall
Kolmogorov-Smirnov(a)
Statistic
df
Sig.
6
.247
.200(*)
6
.279
.157
6
.183
.200(*)
6
.220
.200(*)
6
.345
.024
.360
6
.015
.358
6
.015
.302
6
.092
.400
6
.003
6
.226
.200(*)
* This is a lower bound of the true significance.
10
Shapiro-Wilk
Statistic
df
.832
6
.824
6
.944
6
.899
6
.692
6
.735
6
.736
6
.781
6
.677
6
.837
6
Sig.
.112
.096
.691
.366
.005
.014
.014
.039
.004
.123
Table 3: Relationship between hydrological variables and relative abundance of fish species
m.longirostris
t.rendalli
s.robustus
c.gariepinus
Lake level
Capacity
Outflow
Rainfall
r
Sig. (2-tailed)
r
Sig. (2-tailed)
r
Sig. (2-tailed)
r
Sig. (2-tailed)
r
Sig. (2-tailed)
r
Sig. (2-tailed)
r
Sig. (2-tailed)
r
Sig. (2-tailed)
m.longirostris
1.00
.
-.274(*)
.031
.113
.382
-.135
.295
.132
.375
.152
.247
.219
.293
.268
.268
t.rendalli
-.274(*)
.031
1.00
.
.438(**)
.000
.488(**)
.000
-.570(**)
.000
-.519(**)
.000
.519(**)
.008
.260
.282
s.robustus
.113
.382
.438(**)
.000
1.00
.
.663(**)
.000
-.193
.194
-.187
.151
.144
.493
.139
.571
c.gariepinus
-.135
.295
.488(**)
.000
.663(**)
.000
1.00
.
-.158
.289
-.180
.169
.249
.229
.191
.433
r Spearman's rho correlation coefficient
* Correlation is significant at the 0.05 level (2-tailed).
** Correlation is significant at the 0.01 level (2-tailed).
11
Level
.132
.375
-.570(**)
.000
-.193
.194
-.158
.289
1.00
.
.959(**)
.000
-.789(**)
.002
.086
.872
Capacity
.152
.247
-.519(**)
.000
-.187
.151
-.180
.169
.959(**)
.000
1.00
.
-.056
.789
.325
.175
Outflow
.219
.293
.519(**)
.008
.144
.493
.249
.229
-.789(**)
.002
-.056
.789
1.00
.
.414
.078
Rainfall
.268
.268
.260
.282
.139
.571
.191
.433
.086
.872
.325
.175
.414
.078
1.00
.
FIGURES
b.aenus
o.niloticus
l.cylindricus
m.macrolepidotus
o.mosambicus
o.machrochir
ju
n
no
v
ju
n
ar
au
Ja g
n05
t
m
oc
de
c
m
ay
ju
ly
fe
b
au
g
ar
m.salmoides
m
p
40000
35000
30000
25000
20000
15000
10000
5000
0
se
cpue (g/day)
Figure 2: Location of Lake Mutirikwi in Zimbabwe
c.gariepinus
s.robustus
t.rendalli
year
m.longirostris
Figure 2: relative abundance of fish species caught in Lake Mutirikwi.
12
Figure 3: Regression of cpue of c.gariepinus on ripe species.
Figure 4: Regression of cpue of t.rendalli on capacity
13
Size distribution of c. gariepinus by type of setting
80
60
50
40
30
bottomset
deepnet
topset
Figure 5: Size distribution of c.gariepinus
S iz e d istrib utio n o f m .longiro stris by type o f se tting
60
50
Total length (cm)
total length (cm)
70
40
30
20
to ps e t
de e pne t
b ottom s e t
Figure 6: Vertical size distribution of m .longirostris
14
Size distribution of s.robustus by type of setting
50
45
Total length (cm)
40
35
30
25
20
topset
deepnet
bottomset
Figure 7: Vertical size distribution of s.robustus
Size distribution of t.rendalli by type of setting
40
Toatl length (cm)
35
30
25
20
15
topset
deepnet
bottomset
Figure 8: Vertical size distribution of t.rendalli
15